IEEE Congress on Evolutionary Computation 2010
DOI: 10.1109/cec.2010.5586215
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Automatic generation method to derive for the design variable spaces for interactive Genetic Algorithms

Abstract: Abstract-In the growing E-commerce market, many online shopping sites have adopted product recommendation systems to expand their business opportunities. We have focused on iGA (interactive Genetic Algorithm) as a solution to product recommendation algorithms. Although iGA is an optimization technique for user's preference through the interaction between systems and users, iGA requires extraction of design variables to apply the product recommendation. Extracting design variables from existing products by hand… Show more

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Cited by 3 publications
(3 citation statements)
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“…This aspect is suitable to trace the user's uncertain and time-varying preference. Also, IEC has been successfully applied to diverse real-world applications, such as music, art, computeraided design, and recommender systems [3]- [5]. However, most research has been conducted by merely applying an IEC instance to the problems of interest.…”
Section: Introductionmentioning
confidence: 99%
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“…This aspect is suitable to trace the user's uncertain and time-varying preference. Also, IEC has been successfully applied to diverse real-world applications, such as music, art, computeraided design, and recommender systems [3]- [5]. However, most research has been conducted by merely applying an IEC instance to the problems of interest.…”
Section: Introductionmentioning
confidence: 99%
“…However, most research has been conducted by merely applying an IEC instance to the problems of interest. For example, the conventional iGA (interactive genetic algorithm) was used to recommend products in the E-commerce market [5]; however, its contribution lies in not iGA itself but an automatic extraction of design variables for iGA. Two information filtering techniques have been widely used in the recommender systems: content-based filtering and collaborative filtering.…”
Section: Introductionmentioning
confidence: 99%
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